In this paper, we propose two new support vector approaches for ordinal regression, which optimize multiple thresholds to define parallel discriminant hyperplanes for the ordinal ...
Abstract. Support vector machines (SVMs) have shown superb performance for text classification tasks. They are accurate, robust, and quick to apply to test instances. Their only po...
Soumen Chakrabarti, Shourya Roy, Mahesh V. Soundal...
Many kernel learning algorithms, including support vector machines, result in a kernel machine, such as a kernel classifier, whose key component is a weight vector in a feature sp...
In this paper, we investigate the role of a biomedical dataset on the classification accuracy of an algorithm. We quantify the complexity of a biomedical dataset using five complex...
We study gender discrimination of human faces using a combination of psychophysical classification and discrimination experiments together with methods from machine learning. We r...
Felix A. Wichmann, Arnulf B. A. Graf, Eero P. Simo...